Background: The average treatment effect (ATE) reported by most randomised clinical trials provides estimates of treatment effects for the theoretical, non-existent average patient. However, ATE may not accurately reflect the outcomes for all subsets of the trial population; some individuals may benefit from the intervention, while others experience worse outcomes or no effect at all. Heterogeneity of treatment effect (HTE) is the non-random and explainable variation in the magnitude or direction of a treatment effect among individuals within a population. Predictive approaches to HTE seek to provide estimates of which treatment of choice is better suited for the individual patient, using regression and/or machine learning techniques. This scoping review aims to investigate the extent to which such predictive approaches to HTE are applied to data from trials on sepsis or septic shock as well as the results of these analyses. Methods: The planned review will be conducted in accordance with the PRISMA extension for scoping reviews. We will search Medline, EMBASE, Central, Cinahl and Google Scholar for studies on sepsis or septic shock in which HTE was analysed using predictive approaches. We plan to chart data regarding trial characteristics, patient demographics, disease severity, interventions, outcomes of interest and ATEs, type of predictive approach for the HTE analysis, results from HTE analysis and whether HTE analysis would change an ATE-based trial conclusion. Results: Studies included in the scoping review will be presented as narrative summaries, supplemented with descriptive statistics of quantitative data. Conclusion: The planned scoping review will systematically investigate, summarise and delineate the existing evidence of analysis of HTE in trials on sepsis or septic shock patients as well as their findings, when performed using predictive approaches.